ClinicalTrials.gov
public full text
Public Domain
Predictive Value of Tumor Microenvironment PET/CT for Response and Prognosis in Aggressive Lymphoma: A Multicenter Study
This multicenter study aims to evaluate the predictive value of tumor microenvironment PET/CT imaging for treatment response and prognosis in patients with aggressive lymphoma. Eligible patients with histologically confirmed aggressive lymphoma will undergo FAPI PET/CT imaging, and selected patients who are candidates for immunotherapy will undergo Grazytracer PET/CT imaging. These imaging methods are intended to assess fibroblast activation protein expression and granzyme B activity in lymphoma lesions, reflecting cancer-associated fibroblasts and cytotoxic T-cell activity in the tumor microenvironment. The study will explore optimal imaging assessment criteria and develop clinical-pathological-imaging models to predict treatment response, prognosis, and the relationship between tumor heterogeneity and refractory or relapsed disease.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses#625451
- Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses#623178
- Splenic FDG PET uptake and CT volume as prognostic biomarkers in diffuse large B cell lymphoma.#625920
- Molecular PD-L1 PET/CT Imaging With 89Zr-atezolizumab in Metastatic Triple Negative Breast Cancer#875137
- Mechanistic Study on the Diagnosis of Esophageal Cancer Lymph Node Metastasis Using Spectral CT, Multimodal MRI, FAPI PET-CT, Pathology, and AI Evaluation System#853983
Record · ID 1184485
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive